Summary. Current demand for accountability and efficiency of healthcare organizations, combined with the greater availability of routine data on clinical care and outcomes, has led to an increased focus on statistical methods in healthcare regulation. We consider three different regulatory functions in which statistical analysis plays a vital role: rating organizations, deciding whom to inspect and continuous surveillance for arising problems. A common approach to data standardization based on (possibly overdispersed) Z -scores is proposed, although specific tools are used for assessing performance against a target, combining indicators when screening for inspection, and continuous monitoring using risk-adjusted sequential testing procedures. We pay particular attention to the problem of simultaneously monitoring over 200000 indicators for excess mortality, both with respect to the statistical issues surrounding massive multiplicity, and the organizational aspects of dealing with such a complex but high profile process.
Ensuring that conservation decisions are informed by the best available data is a fundamental challenge in the face of rapid global environmental change. Too often, new science is not easily or quickly translated into conservation action. Traditional approaches to data collection and science delivery may be both inefficient and insufficient, as conservation practitioners need access to salient, credible, and legitimate data to take action. Open access data could serve as a tool to help bridge the gap between science and action, by providing conservation practitioners with access to relevant data in near real time. Broadscale citizen-science data represent a fast-growing resource for open access databases, providing relevant and appropriately scaled data on organisms, much in the way autonomous sensors do so on the environment. Several such datasets are now broadly available, yet documentation of their application to conservation is rare. Here we use eBird, a project where individuals around the world submit data on bird distribution and abundance, as an example of how citizen-science data can be used to achieve tangible conservation science and action at local, regional, and global scales. Our examination illustrates how these data can be strategically applied to improve our understanding of spatial and temporal distributions of birds, the impacts of anthropogenic change on ecological systems, and creative conservation solutions to complex problems. We raise awareness of the types of conservation action now happening with citizen-science data, and discuss the benefits, limitations, and caveats of this approach.
Summary1. Species monitoring is an essential component of assessing conservation status, predicting effects of habitat change and establishing management and conservation priorities. The pervasive access to the Internet has led to the development of several extensive monitoring projects that engage massive networks of volunteers who provide observations following relatively unstructured protocols. However, the value of these data is largely unknown. 2. We develop a novel cross-data validation method for measuring the value of survey data from one source (e.g. an Internet checklist program) relative to a second, benchmark data source. The method fits a model to the data of interest and validates the model using benchmark data, allowing us to isolate the training data's information content from its biases. We also define a data efficiency ratio to quantify the relative efficiency of the data sources. 3. We apply our cross-data validation method to quantify the value of data collected in eBirda western hemisphere, year-round citizen science bird checklist project -relative to data from the highly standardized North American Breeding Bird Survey (BBS). The results show that eBird data contain information similar in quality to that in BBS data, while the information per BBS datum is higher. 4. We suggest that these methods have more general use in evaluating the suitability of sources of data for addressing specific questions for taxa of interest.
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